Remote Decision Tree Jobs in Bolton

4 of 4 Remote Decision Tree Jobs in Bolton

Data Scientist

bolton, greater manchester, north west england, united kingdom
Hybrid / WFH Options
NearTech Search
Engineers, Product, and Marketing teams to develop reports, capture requirements, and analyse market trends. Key experience: Machine Learning techniques including classification (Random Forest, Decision Trees, regression etc) Python and SQL for data analysis and modelling Microsoft Azure, Power BI, Excel, and PowerPoint for data visualisation and reporting. Experience More ❯
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Pricing Analyst

bolton, greater manchester, north west england, united kingdom
Hybrid / WFH Options
Markerstudy Group
experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative More ❯
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Product Specialist – eLearning / AI – Leeds & Remote

Bolton, Greater Manchester, United Kingdom
Hybrid / WFH Options
Crimson
use your product expertise to reduce barriers to legal knowledge through tools such as e-learning platforms, mobile apps, workflow and decision tree solutions, and AI chatbots. The ideal candidate will have a strong understanding of how technology can solve real-world problems, along with a proactive More ❯
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Pricing Manager

bolton, greater manchester, north west england, united kingdom
Hybrid / WFH Options
Gerrard White
and leverage new and existing data sources; capturing and explaining trends with innovative data features Clearly communicate results and proposed actions to key decision makers across the business Champion and facilitate automation of reporting, data pipelines and quality assurance Manage, coach and mentor team members, driving a culture … and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an More ❯
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